from danlp.models import load_bert_base_model
model = load_bert_base_model()
vectorizerd_text = [model.embed_text(sentence)[1] for sentence in df["TextColumns"]]
I get the following
Some weights of the model checkpoint at C:\Users\Jakob.danlp\bert.botxo.pytorch were not used when initializing BertModel: ['cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.bias', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight']
- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
is that intended i.e should it be ignored or is it a bug?
When running
I get the following
is that intended i.e should it be ignored or is it a bug?